Elemental tracer system for determining the source areas of pollution aerosol

ABSTRACT

A method of determining source areas of pollution aerosol. Selected pollution derived, fine particle tracer elements from within the source region are measured. The measured results are expressed as ratios to one of the tracer elements. A signature of the source region is determined from modes in the logarithmic frequency of the ratios of the tracer elements. Measurements are made of the tracer elements from a receptor region and elemental ratios constructed. The elemental ratios from the receptor region are compared with the signatures from possible source regions to determine the most probable source region.

BACKGROUND AND BRIEF SUMMARY OF THE INVENTION

The routine transport of pollution aerosol through long distances isincreasingly recognized as an important aspect of atmospheric science.Atmospheric transport on the scale of 1000 to 10,000 km is now invokedregularly to explain the results of aerosol studies in rural and remoteareas. P. J. Samsonb, J. Appl. Meteorol 19, 1382 (1980); K. A. Rahn andR. J. McCaffrey, Ann. N.Y. Acad. Sci. 338, 486 (1980); R. D. Borys andK. A. Rahn, Atoms. Environ. 15, 1491 (1981); L. A. Barrie, R. M. Hoff,S. M. Daggupaty, ibid., p. 1407; C. Brosset, Ambio 5, 157 (1976).

But long-range transport has created a new set of interpretive problems.While it is relatively easy to identify pulses of transported pollutionaerosols in remote areas which are otherwise clean, it is oftendifficult or impossible to pinpoint the source areas of these aerosols.(At distances of a few hundred kilometers or more, source areas arenormally much more important than point sources).

Sheer distance can cause problems. For example, it has been extremelydifficult to decide whether the important sources of pollution aerosolobserved at Barrow, Alaska, are located in North America, Europe, orAsia. With air-mass trajectories from these sources being 5000 to 10,000km or more in length and representing travel times of 5 to 10 days ormore, pure meterological techniques have not led to consensus about eventhe continents of origin, much less particular regions within thecontinents. J. M. Miller, Atoms. Environ. 15, 1401 (1981); E. R. Reiter,ibid., p. 1465; D. E. Patterson and R. B. Husar, ibid., p. 1479.

The configuration of sources can also make identification difficult. Inthe northeastern United States, for example, where the source areas ofacid aerosol and precipitation are currently in dispute, distances oftransport are much shorter (1000 km or less) but the spatial pattern ofsources is complex. As a result, trajectories to areas of concern suchas the Adirondacks or New England often pass over several strong sourceareas in their last few hundred kilometers. No available transport modelcan reliably apportion the contributions of these sources to the finalsulfate, acid, or other ubiquitous constituents of the pollutionaerosol.

There is thus a need for a more direct way to identify distant sourcesof pollution aerosol. Such a capability would be of practical as well asscientific importance, because it could be extended ultimately todetermining source areas of acid precipitation. It may cost as much as$20 billion to $100 billion to reduce emissions of sulfur dioxide in theeastern United States over the next decade; controlling the wrongsources would be a very costly error.

The present invention embodies a method to detect regional sources ofpollution on a regional scale. The efforts to date in this field canonly trace individual emitters over smaller distances.

Pollution aerosol contains all elements; no true tracers, or elementsunique to specific source areas, exist. But it is reasonable to expectthe proportions of at least some elements to vary with source areabecause different areas have different mixes of the major aerosolsources (combustion, industry, transportation, and so on), differentmixes of fuels, fuels from different origins, different industrialbases, and different degrees of pollution control. However, the numberof regional elemental signatures, the magnitude of their differences,and the elements involved cannot be predicted; they must be determinedempirically.

In general, regional tracers as used in our invention are constructedand used quite differently from urban tracers. Elemental signatures usedto deduce sources of urban aerosol by receptor-oriented techniques (G.E. Gordon, Environ. Sci. Technol. 14, 792 (1980).) are usually derivedfrom either point sources or specific types of sources (automotiveexhaust, for example). Regional aerosols, by contrast, are mixes of manysources and should thus resemble one another much more than signatureswithin an urban region should. Similarities among pollution aerosolshave been recognized for years (K. A. Rahn, "The chemical compositon ofthe atmospheric aerosol," Technical Report, Graduate School ofOceanography, University of Rhode Island (1976).), and many have doubtedwhether useful regional differences could be found. We have determinedthat characteristic regional signatures do exist, many of which are verydifferent from one another.

The two keys to deriving regional signatures are finding the rightelements and handling the data with the appropriate statisticaltechniques. The "marker-element" approach sometimes used in urbanstudies (where the contribution of a source is evaluated by a singleelement) cannot be used with regional signatures because of their greatsimilarities. The opposite approach, constructing signatures from allavailable elements, is practiced in some urban studies but addes toomuch noise to regional pollution signatures. The best approach seems tobe a compromise-limit regional signatures to those few elements with thegreatest tracer power.

Several requirements should be met by elements and signatures beforethey can be used in a regional tracer system: the elements should bepollution-derived, sampled and measured accurately, emitted stably andhomogeneously in each region, and present on particles small enough tobe transported long distances; each signature should remain recognizableduring transport. Our preliminary assessment indicates that all theserequirements are met adequately; we illustrate several of them in thedescription that follows. Nevertheless, some of these requirements, suchas conservation of proportions during transport, are sufficientlycritical that we have built routine checks into our operating system.

In our invention a system in which the relative abundances of selectedelements in pollution aerosol (suspended particles) are used todetermine the region(s) from which it has originated. The technique canbe applied at distances of hundreds to thousands of kilometers from thesources, i.e., in regions ranging from rural to very remote, and whereconventional approaches such as emission inventories, air-masstrajectories, and long-range transport models fail. For example, bothCanada and the United States now agree that the several long-rangetransport models currently in use for predicting the origins of sulfateand acidity are unverified and unverifiable in the near future. We thusview our elemental technique as a powerful alternative.

Our invention distinguishes from the known prior art in that werecognize and document the existence of regional elemental signatures.The technique described hereinafter represents our formalized method fordeveloping these signatures and using them quantitatively.

The techniques has several key features. It preferably uses sevenpollution-derived, fine-particle elements in the signatures (arsenic,selenium, antimony, zinc, indium, manganese, vanadium). These elementsare chosen from the 40 or so that we can measure by neutronactivationanalysis because they are the most pollution-derived and are determinedbest, i.e., have the lowest analytical uncertainties. This list ofelements is not static; it can be altered as needed, and should expandin the future as other analytical techniques are employed. For elementssuch as manganese and vanadium, a substantial fraction of whose masscomes from suspended soil dust, only the pollution-derived component isused. It is important that only fine-particle elements be used in thistracer system, so that they will remain in the atmosphere for longperiods and their proportions will not change during transport.

Regional signatures are preferrably built from the six elemental ratiosto selenium rather than the seven absolute concentrations. Ratios areused to correct for changes in elemental concentration due to dispersionand removal during transport.

The regional signatures are built up from multiple samples at multiplesites within each region. Because any region can be influenced byaerosol from outside it, only some of the samples from a given regioncan be used to characterize it. They must be chosen from the total setof samples with care. We generally use some combination of a prioriknowledge of the region, modal analysis of the frequency distributionsof the elemental ratios, and meterological analysis to do this. To besafe, the signature of a region should not be considered known untilsamples inside and outside the region agree. From the final set ofsamples representing a region, geometric means and geometric standarddeviations are calculated from each elemental ratio to selenium. Thecollection of six means and six standard deviations is the elementalsignature of that region.

A sample of aerosol from a receptor region can be assigned to amost-likely source area by discriminant analysis, which compares the sixelemental ratios to those of samples from possible source regions in amultivariate sense and assigns probabilities that the sample came fromeach region.

Contributions of several source regions to the signature elements can bedetermined by least-square apportionment, using various calculationalroutines and elemental weighting factors.

Contriubtions of several source regions to sulfate aerosol (formedmostly from SO₂ during transport) or other nonsignature constituents canbe determined by regressing the regional coefficients of a suite ofsamples against their sulfate concentrations.

Unique features of our tracer technique are its set of seven elementsand its regional approach. Elemental tracers have been used to determinethe sources of urban aerosol for several years. Our regional approach,however, uses different elements, a different form for the signatures,builds up the signatures according to a different protocol, andmanipulates them with different statistical techniques.

We have determined that well-defined regional signatures exist in bothNorth America and Europe. In North America, we have measured bothmidwestern and coastal influences on pollution aerosol at Underhill,Vt.; Narragansett, R. I.; High Point, N. J.; and Allegheny Mountain, Pa.The meterology of many of the samples in question was sufficientlyobscure that it could not have revealed their origins with anyconfidence. In Vermont, the majority of the sulfate aerosol in summercomes from the Midwest; in Rhode Island, it comes from the Northeast. Wehave also detected a signature from the nonferrous smelters of theSudbury Basin and shown that their contributions to sulfate aerosol inNew England during summer are small. The role of these smelters has beendiscussed for years; we have provided the first direct answers. InEurope, we have shown that the aerosol of a particularly strongpollution episode in Sweden and Finland came from East Europe, not WestEurope or the United Kingdom. In the Arctic, we have shown that aerosolat both Barrow, Alaska and Bear Island (Norwegian Arctic) is dominatedby Eurasian rather than North American sources. At each site, aerosolsfrom different parts of Eurasia have been detected.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1a, 1b, 1c, 1d, 1e and 1f show the frequency distributions of sixelemental ratios at six sites in eastern North America, Europe, ad theArctic; and

FIG. 2 shows the observed and predicted sulfate for 21 semiweeklysamples during June tp September 1979.

DESCRIPTION OF THE PREFERRED EMBODIMENT

The first regional tracer was the noncrustal Mn/V ratio Atoms, Environ.15, 1457 (1981). (The noncrustal component of an element is used here tomean the mass present in excess of that calculated from a crustalreference element like Al, Si, Fe or Ti, assumed to be totally crustalin the aerosol (a), and a crustal reference material such as bulk rockor soil (r). The formula typically used to calculate the noncrustalcomponent of element X is

    Noncrustal X.sub.a =total X.sub.a -Al.sub.a (X/Al).sub.r

In most cases, global mean crustal rock or soil is satisfactory;occasionally, local rock or soil must be used as reference material).This tracer was designed to determine whether Arctic aerosol originatedmainly from Europe or eastern North America. The noncrustal Mn/V ratiodemonstrated the general feasibility of regional elemental tracers andstimulated the development of more sophisticated tracing systems. Atpresent, we are using a seven-element tracer system involving As, Sb,Se, Zn, In, noncrustal Mn, and noncrustal V. The design of this systemand several of its applications are discussed below.

These seven elements were chosen from the 40 to 45 that we have measuredby neutron activation as best meeting the criteria of beingpollution-derived, fine-particle (The dividing line between fine andcoarse aerosol is usually taken to be radius ˜1 μm. This corresponds tothe approximate breakpoint between (i) particules which penetrate to thelung and those which do not, (ii) coarser particles formed by mechanicalsubdivision (of soil and seawater, for example) and finer particlesformed by coagulation or nucleation, and (iii) the original German"large" and "giant" ranges of particles.), and accurately analyzable(Instrumental neutron activation normally allows As, Sb, Se, Zn, andnoncrustal V to be determined in replicate aerosol samples touncertainties of 5 to 15 percent, and In and noncrustal Mn to 10 to 40percent. Differences between elements in simultaneous samples areusually less than 10 percent; for ratios, most of this differencedisappears.). Potential tracers rejected because of larger analyticaluncertainties included Cu, Ni, Ga, Mo, Ag, Cd, Sn, W, Au, and Hg. Withbetter analysis, any or all of these might be included in the system.Lead and elemental carbon are strong candidates which should also beinvestigated. Indium, whose analysis is poorer than those of the othersix elements, was retained because of its great utility in tracingnonferrous smelters, K. A. Rahn, N. F. Lewis, D. H. Lowenthal, inReceptor Models Applied to Contemporary Pollution Problems, SP-48, AirPollution Control Association, Pittsburgh, PA, 1982 p. 163.

Our regional signatures consist of six elemental ratios to Se. Ratiosare used to normalize for variable meterological effects such asdispersion and removal; Se is used in the denominator because it is ageneral pollutant found at similar concentrations in diverse sourceareas and hence will not bias the ratios toward any particular region.In spite of Se's ubiquitous but modest vapor phase of 15 to 30 percentnear the surface (B. W. Mosher and R. A. Duce, J. Geophys. Res. 88, 6761(1983).) and its natural sources such as volcanoes, it works well as anormalizing element in regions as remote as the Arctic in winter. Wetested Zn as an alternative denominator (because of its similarly lowcoefficient of variation) and obtained the same results as with Se.Other general pollution elements such as Pb or C might also beconsidered for the denominator.

The signature of a source region cannot be derived in a completelystraightforward fashion because most regions can be affected bypollution aerosols transported from other regions. To eliminate suchinterference, we have developed a protocol which involves multiplesamples at multiple sites inside and outside the region. At each site,at least 100 (ideally) daily samplers are taken and analyzed for thetracer elements. Logarithmic frequency distributions of the various X/Seratios are then constructed and examined for the presence of modes, ormaxima, which represent characteristic aerosols for the sites. Themeterological characteristics such as of atmospheric stagnation can becombined with chemical characteristics of the samples in a mode to givea good idea of its source. By combining the modal information fromseveral sites in a region, its aerosol may usually be distinguished fromthose transported from neighboring regions. Local aerosol may also beidentified from periods of atmospheric stagnation. As a final check,regional signatures are verified by sampling downwind of the region.This also shows whether any elemental ratios change significantly duringtransport.

To date, we have used filter samples of total aerosol for our tracersystem. In effect, this provides size-segregated data because the tracerelements chosen are mostely submicrometer. True fine-particle sampleswould probably improve the tracer system by reducing the variability ofelemental ratios and allowing mixed-mode elements such as Fe, Co, and Crto be considered. But how much the improvement would be is not yetknown, and size-segregated samples are much smaller and not readilyavailable from many regions of interest. When elemental tracertechniques are eventually applied to precipitation, total aerosol willbe a more appropriate reference than fine-particle aerosol, for coarseparticles are scavenged more efficiently by precipitation than are fineparticles.

Factor analysis, while useful for understanding broad elementalrelations and the general sources of pollution aerosol of a site, hasnot been particularly successful in selecting elements as tracers ordefining regional signatures. The reason for this seems to be that anytechnique which is based solely on single measures of similarity betweenelements (such as correlations) in a collection of samples does notadequately reveal the complex relations implicit in mixed frequencydistributions.

FIG. 1 shows the six X/Se distribution for six sites at which we havereasonable amounts of data: Narragansett, R. I., and Underhill, Vt., ineastern North America; Kecskemet, Hungary, and Rorvik, Sweden, inEurope; and Barrow, Alaska, and Bear Island, Norway, in the Arctic(Seventy-nine Narragansett samples taken semi-weekly duringFebruary-April and June-August 1978 and January-March and June-September1979; 43 Underhill samples taken daily during July-August 1982; 76Rorvik samples taken for 1 to 3 days each during fall and winter1981-1982; 31 Kecskemet samples taken daily during fall and winter1981-1982; 66 Bear Island samples taken for 2 to 3 days each duringwinter 1977-1978; 54 Barrow samples taken simiweekly from October 1977to May 1978). Depending on element and location, one or more modes areseen in each distribution. The modes are reasonably symmetric (that is,log-normal), with geometric standard deviations of 1.4 to 1.6 (68percent of the points found within a total factor of 2 to 3). Some modeshave geometric standard deviations as low as 1.2. The presence of thesemodes shows that a few major types of pollution aerosol are found ateach site.

More types of pollution aerosol may be present at a site than arerevealed directly by the major modes, however. Broader-than-normal modesmay be composed of two or more unresolved modes, as seems often to bethe case for Zn/Se and Sb/Se, for example. Small features may representinfrequent appearances of aerosols which are more important elsewhere.An example of this is the small upper mode of As/Se at Rorvik (ratios of8 to 10), which coincides with the principal mode (6 to 12) at Kecskemet(we show below the upper mode at Rorvik was created by a pulse ofaerosol from eastern Europe). Another example is the low shoulder ofZn/Se at Narragansett (ratios of 10 to 20), which has been resolved intoa discrete mode by subsequent shorter period samples. The real number ofmodes in most distributions is not known and may be considerably largerthan the number apparent from FIG. 1.

Membership in most modes is organized; that is, samples in a certainmode of one distribution are usually found together in otherdistributions. For example, the samples from eastern Europe whichcomprise the upper As/Se mode of Rorvik also comprise the low shoulderof noncrustal V/Se there (ratios of 3 to 6). This illustrates thatwell-defined pullution aerosols with recognizable signatures do exist.As shown below, they can usually be identified with specific geographicsource areas.

At present, we use the modes of FIG. 1 only qualitatively. To derivesignatures of pollution aerosol for specific regions, we use subsets ofthe modes composed of samples deemed most representative. Withexperience, it should be possible to increase the numbers of samplesused to define signatures.

Twelve regional signatures, six from North America and six from Europe,are shown in Table 1. The signature of regional New England (NE) wasderived from four daily samples at Underhill Aug. (4 to 7 1982), in agedCanada air masses which had not been affected by the large nonferroussmelters of the Sudbury Basin. The outstanding feature of this signatureis its low As/Se ratio, which we interpret as indicating minimal coalinfluence. We have also detected this signature in Narragansett andSouth Portland, Me. (the small low-As mode at Narragansett in FIG. 1 isassociated with this kind of aerosol.

                                      TABLE 1                                     __________________________________________________________________________    Geometric mean elemental signatures for source aerosols in North America      and Europe                                                                    (geometric standard deviations in parentheses).                                                  Noncrustal Noncrustal                                                                          In/Se                                     Source                                                                              N  As/Se                                                                              Sb/Se                                                                              V/Se  Zn/Se                                                                              Mn/Se (× 1000)                            __________________________________________________________________________    Individual sources                                                            SCANS 5  2.8 (1.3)                                                                          0.94 (2.0)                                                                         24 (1.3)                                                                            43 (1.5)                                                                           5.2 (1.8)                                                                           9.5 (1.7)                                 WEURS 5  1.88 (1.2)                                                                         1.01 (1.4)                                                                         5.8 (1.3)                                                                           37 (1.1)                                                                           6.5 (1.2)                                                                           13.1 (1.6)                                WEURH 5  3.5 (1.1)                                                                          0.75 (1.3)                                                                         7.2 (1.8)                                                                           56 (1.4)                                                                           6.8 (1.7)                                                                           11.1 (2.2)                                EEURF 5  7.2 (1.2)                                                                          1.33 (1.3)                                                                         7.8 (1.2)                                                                           54 (1.1)                                                                           10.0 (1.2)                                                                          13.1 (1.3)                                EEURS 3  7.3 (1.1)                                                                          1.73 (1.1)                                                                         4.8 (1.2)                                                                           66 (1.1)                                                                           13.7 (1.2)                                                                          15.1 (1.2)                                EEURH 4  8.9 (1.0)                                                                          1.18 (1.1)                                                                         5.2 (1.3)                                                                           48 (1.1)                                                                           8.9 (1.8)                                                                           9.8 (1.4)                                 NE    4  0.13 (1.4)                                                                         0.45 (1.3)                                                                         11.3 (1.2)                                                                          32 (1.2)                                                                           9.2 (1.3)                                                                           9.8 (1.9)                                 BOS   3  0.68 (1.5)                                                                         0.82 (1.8)                                                                         35 (1.2)                                                                            37 (1.1)                                                                           4.1 (1.2)                                                                           5.3 (1.1)                                 NYC   3  1.10 (1.1)                                                                         1.63 (1.7)                                                                         11.1 (1.3)                                                                          40 (1.1)                                                                           6.5 (1.3)                                                                           9.6 (1.6)                                 WASH  4  1.46 (1.2)                                                                         0.82 (1.2)                                                                         9.9 (1.2)                                                                           22 (1.2)                                                                           4.0 (1.8)                                                                           7.1 (1.2)                                 INT   4  0.92 (1.2)                                                                         0.28 (1.4)                                                                         1.96 (1.4)                                                                          10.8 (1.3)                                                                         2.6 (1.5)                                                                           3.9 (1.7)                                 SONT  3  8.0 (1.2)                                                                          0.75 (1.2)                                                                         1.77 (1.9)                                                                          57 (1.1)                                                                           13.9 (1.1)                                                                          46 (1.7)                                  Regional means                                                                SCANS 5  2.8 (1.3)                                                                          0.94 (2.0)                                                                         24 (1.3)                                                                            43 (1.5)                                                                           5.2 (1.8)                                                                           9.5 (1.7)                                 WEUR  10 2.6 (1.4)                                                                          0.87 (1.4)                                                                         6.4 (1.6)                                                                           45 (1.4)                                                                           6.6 (1.5)                                                                           12.1 (1.9)                                EEUR  12 7.8 (1.2)                                                                          1.37 (1.2)                                                                         6.0 (1.4)                                                                           54 (1.1)                                                                           10.4 (1.5)                                                                          12.3 (1.3)                                ECOAST                                                                              14 0.58 (2.9)                                                                         0.80 (1.8)                                                                         13.8 (1.7)                                                                          31 (1.3)                                                                           5.7 (1.6)                                                                           7.8 (1.6)                                 INT   4  0.92 (1.2)                                                                         0.28 (1.4)                                                                         1.96 (1.4)                                                                          10.8 (1.3)                                                                         2.6 (1.5)                                                                           3.9 (1.7)                                 SONT  3  8.0 (1.2)                                                                          0.75 (1.2)                                                                         1.77 (1.9)                                                                          57 (1.1)                                                                           13.9 (1.1)                                                                          46 (1.7)                                  Continental means                                                             EUR   27 4.2 (1.8)                                                                          1.08 (1.5)                                                                         8.0 (1.9)                                                                           49 (1.3)                                                                           7.6 (1.6)                                                                           11.6 (1.6)                                NAMER 21 0.93 (3.5)                                                                         0.65 (1.9)                                                                         7.1 (3.0)                                                                           28 (1.8)                                                                           5.6 (1.9)                                                                           8.8 (2.4)                                 __________________________________________________________________________

The "Boston" (BOS) aerosol was derived from three daily samples atNarragansett when the winds came from the direction of Boston andProvidence and SO₂ concentrations were high (July, 20 and Aug. 3 and 61982). The New York City (NYC) signature came from six semiweeklysamples taken in midtown Manhattan during the 1977-1978 winter. In orderto better apply this signature to summer samples elsewhere, we reducedits noncrustal V by 50 percent (K. A. Rahn, D. H. Lowenthal, and N. F.Lewis ["Elemental tracers and source areas of pollution aerosol inNarragansett, Rhode Island." Technical Report, Graduate School ofOceanography, University of Rhode Island (1982)] show that noncrustal Vin both New York City and Narragansett decreases from winter to summerby 50 percent relative to other pollution-derived elements.) To bettersimulate the regional signature near New York, we reduced the Zn, whichis abnormally enriched in urban aerosol, by 30 percent (because roughly30 percent of the Zn is from coarse particles and presumably local, notregional, there). The Washington, D.C. (WASH), signature came from grandaverages of individual average concentrations from ten sites in theWashington area during August and September 1976 (G. S. Kowalczyk, G. E.Gordon, S. W. Rheingrover, Environ.Sci. Technol. 16, 79 (1982). As inNew York, Zn was reduced by 30 percent in an attempt to representaerosol from the central mid-Atlantic states. The interior (INT)signature was derived from four daily samples in Underhill, Vermont, inJuly 1982, when an unusually strong signal of coal was present andassociated with winds from the south-southwest. This singature does notrepresent pure coal emissions but rather an area where coal emissionsare unusually strong. The Canadian smelter (SONT) signal was derivedfrom three samples in southern Ontario roughly 300 km east-southeast ofSudbury (K. A. Rahn, thesis, University of Michigan (1971). It isenriched in As and In. (The small groups of samples defining thesignatures were representative distillations of larger sets of data;numbers of samples in each group were kept comparable for statisticalpurposes).

The samples from Kecskemet and Rorvik allowed us to construct sixregional signatures for Europe, three from the East and three from theWest. Signature EEURH came from four samples associated with the mostprominent mode of As/Se in Kecskemet. Signature EEURS came from threesamples at Rorvik during the most intense "black episode" (C. Brosset,Supra) of the past decade.

                                      TABLE 2                                     __________________________________________________________________________    Episode of east European aerosol at Sweden and Finland.                                             Non-    Non-                                            Dates of Sample                                                                        Sulfate      crustal crustal                                                                           In/Se                                       (1982)   (μg m.sup.-3)                                                                   As/Se                                                                             Sb/Se                                                                             V/Se                                                                              Zn/Se                                                                             Mn/Se                                                                             (× 10.sup.3)                          __________________________________________________________________________    Rorvik, Sweden                                                                11-13 January                                                                          2.4  3.0 0.67                                                                              15.4                                                                              69  13.1                                                                              17.4                                        13-15 January                                                                          5.4  9.6 2.4 50  52  26.5                                                                              31                                          15-18 January                                                                          12.9 4.0 0.8 5.2 49  6.0 <3                                           18-20 January*                                                                        11.1 7.4 1.85                                                                              6.0 70  13.0                                                                              16.1                                         20-21 January*                                                                        19.5 8.2 1.68                                                                              3.8 65  11.7                                                                              12.8                                         21-22 January*                                                                        35.5 6.3 1.68                                                                              4.8 63  16.8                                                                              16.7                                        22-25 January                                                                          8.3  3.3 1.83                                                                              4.2 33  4.5 7.6                                         25-27 January                                                                          3.6  1.8 0.98                                                                              14.6                                                                              31  3.5 13.1                                        Ahtari, Finland                                                               17-18 January                                                                          6.5  3.4 0.60                                                                              9.4 54  3.8 7.2                                         18-19 January                                                                          5.3  2.6 0.64                                                                              8.0 66  5.7 11                                           19-20 January*                                                                        3.7  5.5 1.3 8.9 58  9.5 15                                           20-21 January*                                                                        19.4 6.6 1.6 5.7 52  13  13                                           21-22 January*                                                                        9.0  6.8 1.5 7.0 56  11  11                                           22-23 January*                                                                        17.8 5.9 1.6 8.3 52  10  10                                          23-24 January                                                                          0.95 4.6 0.86                                                                              10  52  7.6 18                                          __________________________________________________________________________     *East European aerosol present.                                          

As shown in Table 2, this aerosol was very different from that beforeand after the episode and had eastern European rather than westernEuropean characteristics. These samples made up most of the small uppermode of As/Se at Rorvik shown in FIG. 1. Signature EEURF came from foursamples at Ahtari, southern Finland, during the same black episode.Table 2 also shows these samples and how they closely resembled aerosolat Rorvik during the same period. The two signatures of western Europe,WEURS and WEURH, were derived from five samples at Rorvik when the windswere from the southwest and fine samples at Kecskemet when the windswere from the west, respectively. For at least As/Se and noncrustalV/Se, these samples appeared in well-defined modes at the two sites. Thelast European signature is for Scandinavia (SCANS), as determined fromperiods of unusually high noncrustal V/Se at Rorvik, which usuallycoincided with weak circulation or winds from the north.

The western and eastern European signatures confirm the existence ofgeneral regional aerosols which appear at various sites in and aroundlarge source regions. Because the three eastern signatures are sosimilar, they can be combined into a general eastern European signature(EEUR), as shown in Table 1. Similarly, the two western Europeansignatures can be combined into the general WEUR. As more data becameavailable from eastern North America, it should be possible to constructgeneral signatures there as well. For illustrative purposes, we havecombined the four coastal signatures NE, BOS, NYC, and WASH into ECOAST,which is also shown in Table 1. (All samples from North America andEurope were combined to form the continental signatures NAMER and EUR.)Note that the principal modes of As/Se, noncrustal V/Se, and Zn/Se atBarrow and Bear Island agree quite well with the WEUR and EEUR modes atRorvik and Kecskemet.

Some of the most significant features emerging from elemental tracersare that the tracing power varies widely from element to element, thatmost of the tracing power is vested in a very few elements, and that thediscriminatory power of an element, as measured by the range of its X/Seratio and its degree of modality, is similar at widely diverse sites.For example, As/Se and Zn/Se have, respectively, large ranges withwell-defined multiple modes and small ranges with single modes at mostsites. Thus some elements are inherently much better tracers thanothers. The reasons for this are probably geochemical. They may berelated to large-scale elemental variations in the earth's crust.

                  TABLE 3                                                         ______________________________________                                        Two estimates of the relative discriminatory power of                         various elemental ratios on the 48 signature samples of                       Table 1.                                                                                   Number of samples misclassified                                               (out of 48)                                                                     With 12   With 6    With 2                                                    individual                                                                              regional  continental                                Elemental ratio omitted                                                                      signatures                                                                              signatures                                                                              signatures                                 ______________________________________                                                       1         2         7                                          As/Se          6         13        13                                         Sb/Se          1         2         6                                          Noncrustal V/Se                                                                              3         6         7                                          Zn/Se          2         3         9                                          Noncrustal Mn/Se                                                                             1         4         7                                          In/Se          2         2         7                                          As/Se, noncrustal V/Se                                                                       13        19        10                                         Noncrustal Mn/Se, In/Se*                                                                     2                                                              Sb/Se, Zn/Se*            5                                                    Sb/Se, Zn/Se, noncrustal           8                                          Mn/Se, In/Se*                                                                 ______________________________________                                         *Ratios indicated by stepwise discriminant analysis to be lacking in          discriminatory power.   Table 3 illustrates two ways to measure the           relative discriminatory power of tracer elements. In the first, linear     discriminant analysis (Linear discriminant analysis is used to define     groups from observations with known attributes and then classify other     observations into one of these grops (D. F. Morrisson, Multivariate     Statistical Methods (McGraw Hill, New York, 1976). pp. 230-246). For     linear discriminant analysis, we used a program in SAS-79 (SAS) Institute,     Inc., Cary, NC 1979) on log-transformed data was used to classify the 48     signature samples of Table 1 into the 12, 6 and 2 groups shown in Table 3.     Initially, all six of our X/Se ratios were used. Then the samples were     reclassified with each of the ratios removed in turn. The greater the     discriminatory power of a ratio, the more samples will be misclassified     when it is removed. The results showed that As/Se and noncrustal V/Se had     the greatest discriminatory power, Zn/Se had somewhat less power, and the     other three ratios contributed little or nothing on the average. When both     As/Se and noncrustal V/Se were removed, the extent of misclassification     became greater than their summed individual effects. As a more     sophisticated test of discriminatory power, stepwise discriminant analysis     (In stepwise discriminant analysis, variables are added to the     discriminant function in the order that they enhance the separation     between groups. For stepwise discriminant analysis, we used a program in     BMDP, "Biomedical Computer Programs, P-Series" (Univ. of California Press,     Berkeley, 1979)) was applied to the six ratios (log-transformed) as they     were used to segregate the 48 samples into groups of 12, 6, and 2     signatures. The results are shown at the bottom of Table 3. The only two     ratios having good tracer power in all three cases were As/Se and     noncrustal V/Se.

It may be possible to improve the discriminatory power of our ratios byusing discriminant analysis in which elemental ratios are replaced byhigher order terms as generated and selected by the group method of datahandling (A. G. Ivakhnenko et al, in Theoretical Systems Ecology, E.Halfon, Ed. (Academic Press, New York, 1979), p. 325). Thediscriminatory power of optimized functions of ratios seems to be atleast 20 to 40 percent greater than that of linear functions. Productsinvolving As/Se and noncrustal V/Se are the most useful.

Empirical confirmation that certain elements are crucial to a successfulregional tracer system was obtained by comparing our experience insouthern Sweden with results of Lannefors et al. H. Lannefors, H. C.Hansson, L. Granat, Atoms. Environ. 17, 87 (1983) who took daily aerosolsamples for 1 year at Sjoangen, 200 km northeast of Rorvik. Their data,which included S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, and Pbbut lacked As, Se, Sb, and In, were unable to differentiate betweenaerosols from eastern and western Europe.

To test whether the criteria on which our seven-element tracer systemwas based--that the components be pollution-derived, fine-particle, anddetermined well by neutron activation--are unduly restrictive, weinvestigated the tracer power of nine other elements (Al, Sc, Cr, Co,Fe, La, Ce, Sm, Th) by means of stepwise discriminant analysis on thesame 48 signature samples. These elements are as well determined as theseven basic tracers but are mostly coarse-particle in the aerosol (Cr,Co, and Fe usually have a fine-particle component and La and Ceoccasionally do). In general, the tracer power of La, Ce and Sc wascomparable to or better than that of Sb, In, and noncrustal Mn but lessthan that of As, noncrustal V, and Zn. The Al, Sm, and Th appeared tohave little promise as tracers, and Fe, Co, and Cr behaved in anintermediate fashion. We do not know how the apparent tracer power ofLa, Ce and Se is partitioned between their coarse and fine-particlecomponents. The fraction associated with coarse aerosol may be lessuseful than suggested by these signature samples, because coarse aerosolis not transported as efficiently as fine aerosol. Overall, it isprobably prudent to measure as many elements as possible (both naturaland pollution-derived) in the aerosol, with an eye toward occasions whenthey could be useful as tracers. Dust storms, volcanic eruptions, orbursts of aerosol from unexpected point sources of pollution may allprovide transient aerosols with unusual signatures which could beunderstood by use of additional tracer elements.

Once discriminant analysis has been used to determine classificationcriteria from samples with distinctive signatures, one may classifynonsignature samples into those groups. In principle, the orginin of anaerosol sample could be determined from its chemical composition alone.

                                      TABLE 4                                     __________________________________________________________________________    Classification of nonsignature aerosol samples in North                       America and Europe.                                                                      Classification                                                                With 12           With 2                                                      Individual                                                                             With 6 Regional                                                                        Continental                                                 Signatures                                                                             Signatures                                                                             Signatures                                                  North    North    North                                                       America                                                                            Europe                                                                            America                                                                            Europe                                                                            America                                                                            Europe                                      __________________________________________________________________________    Narragansett, R.I.                                                                       98    3  92    9  94    7                                          Underhill, Vermont                                                                       25   10  22   13  29    6                                          Rorvik, Sweden                                                                           21   45  19   47  28   38                                          Kecskemet, Hungary                                                                        0   22   0   22   0   22                                          With five regional signatures                                                 Bear Island, Norway  1   31                                                   (without In/Se)                                                               Barrow, Alaska       5   28                                                   (without In/Se)                                                                          SONT NE  BOS  NYC WASH INT                                         Narragansett. R.I.                                                                        0   17  17    8  37   22                                          Underhill, Vermont                                                                        1   14   1    7   3    9                                          __________________________________________________________________________

Table 4 shows a geographic classification of unknown samples by ourseven-element tracer system. In the upper part of the table,nonsignature samples from Narragansett, Underhill, Rorvik, and Kecskemethave been classified as North American or European based first on 12individual signatures, then on six regional signatures, and finally onthe two continental signatures of Table 1. In general, the posteriorprobability for membership in one of the source groups was greater than90 percent. All samples from Kecskemet were classified correctly (asEuropean). At Narragansett, 90 to 95 percent were classified correctly(as North American). At Underhill and Rorvik, however, only 60 to 80percent were classified correctly. Similar results were obtained whenthe noncrustal Mn/Se and In/Se ratios were eliminated. Classifyingsamples by continent is a severe test, however, because it is much moredifficult for entire continents than for regions to have distinctsignatures.

The center of Table 4 shows how samples at Bear Island and Barrow wereclassified relative to the five more appropriate regional signatures(SCANS, WEUR, EEUR, ECOAST, INT). Only 1 of 32 (3 percent) and 5 of 33(15 percent), respectively, were called North American. This confirmsour earlier conclusions, reached independently, that Arctic pollutionaerosol is strongly Eurasian in origin K. A. Rahn, ibid. 15, 1447(1981); Idojaras 86, 1 (1982).

The bottom of Table 4 illustrates how the nonsignature samples atNarragansett and Underhill were classified relative to the six NorthAmerican signatures. At Narragansett, the four coastal signaturesaccounted for three-quarters of the cases, with the other quarter comingfrom the interior signature. This result confirms with multielementaldata the conclusions about dominance of coastal aerosol reached earlierfrom noncrustal Mn and V alone K. A. Rahn, D. H. Lowenthal, and N. F.Lewis ["Elemental Tracers and source areas of pollution aerosol inNarrangansett, Rhode Island.", Technical Report, Graduate School ofOceanography, University of Rhode Island (1982)]. At Underhill, on theother hand, the most common signature is New England (40 percent),followed by other East Coast (30 percent) and the interior (25 percent).Considering Underhill's location in northern New England, thisdistribution of sources is reasonable.

                                      TABLE 5                                     __________________________________________________________________________    Elemental concentrations in five source-area aerosols.                                Concentration (ng m.sup.-3)                                           Element NE      BOS     NYC     WASH   INT                                    __________________________________________________________________________    As      0.060 ± 0.033                                                                      0.49 ± 0.15                                                                        2.0 ± 0.2                                                                          3.2 ± 0.9                                                                         1.54 ± 0.40                         Sb      0.143 ± 0.048                                                                      0.83 ± 0.41                                                                        3.1 ± 0.6                                                                          2.1 ± 0.7                                                                         0.55 ± 0.29                         Se      0.37 ± 0.20                                                                        1.00 ± 0.60                                                                        1.88 ± 0.42                                                                        2.4 ± 0.7                                                                         1.78 ± 0.79                         Noncrustal V                                                                          4.0 ± 1.7                                                                          35 ± 6                                                                             20 ± 4                                                                             23 ± 8                                                                            3.4 ± 1.0                           Zn      11.1 ± 4.3                                                                         37 ± 3                                                                             70 ± 17                                                                            60 ± 12                                                                           18.2 ± 8.0                          Noncrustal Mn                                                                         2.2 ± 0.3                                                                          4.2 ± 0.8                                                                          13.0 ± 1.1                                                                         9.2 ± 3.4                                                                         4.3 ± 2.4                           In      0.0028 ± 0.0001                                                                    0.0050 ± 0.0040                                                                    0.0160 ± 0.0032                                                                    0.020 ± 0.006                                                                     0.0064 ± 0.0006                     __________________________________________________________________________

                                      TABLE 6                                     __________________________________________________________________________    Contributions of various source regions to elements in                        Narragansett aerosol sample GSO 176, 3 to 8 August                            1979.                                                                                Weight-                                                                            Concentration (ng m.sup.-3)                                              ing                     Total                                                 Factor                                                                             NE   BOS  WASH                                                                              INT  predicted                                                                          Observed                                  __________________________________________________________________________    As     300  0.03 0.06 0.20                                                                              0.36 0.65 0.67                                      Sb      30  0.08 0.10 0.13                                                                              0.13 0.44 0.55                                      Se     100  0.20 0.13 0.15                                                                              0.42 0.90 0.90                                      Noncrustal V                                                                          20  2.20 4.42 1.44                                                                              0.80 8.9  9.0                                       Zn      4   6.11 4.68 3.76                                                                              4.31 18.9 18.4                                      Noncrustal                                                                              0.4                                                                             1.21 0.53 0.58                                                                              1.02 3.34 2.00                                      In     100   0.0015                                                                             0.0006                                                                            0.00                                                                               0.0015                                                                             0.0036                                                                             0.0040                                   __________________________________________________________________________

Discriminant analysis is used to determine which of several signaturesis most likely to account for an aerosol sample. In actuality, however,most aerosol samples come from more than one source, either because ofthe history of the air mass or because of changes in it during sampling.By using least-squares techniques similar to those employed in previouschemical element balance analyses G. E. Gordon, Environ. Sci. Technol.14, 792 (1980), a sample can be apportioned among the various regionalaerosols which may have contributed to it (For least-squaresapportionments of aerosol we used the program PETMIX, originallydeveloped for petrologic studies [T. L. Wright and P. C. Doherty, Geol.Soc. Am. Bull. 81, 1995 (1970)], and a program in SAS-79). For theelemental concentrations of five regional aerosols listed in Table 5(Tables 5 to 7 are from K. A. Rahn and D. H. Lowenthal, paper presentedat the 17th Annual Conference on Trace Substances in EnvironmentalHealth, Columbia, Mo., June 13 to 16 1983, published May 1984.), Table 5shows an apportionment for an August 1979 aerosol sample fromNarragansett. In this sample, the abundances of six of the seven tracerelements were accounted for to better than 20 percent by four of thesignatures (NYC gave a negative coefficient, so it was eliminated andthe regression was rerun with four sources). The weighting factor inTable 6 is really two factors, one to scale the numerical values of thedifferent elements and another, based on Table 3, to weight, As, Se,noncrustal V, and Zn relative to Sb, In, and noncrustal Mn. (The finalapportionment is insensitive to weighting factor, however.) Note thatabout half of the As and Se were associated with the interior signal,whereas 60 to 80 percent of the Sb, Zn, In, and noncrustal Mn and morethan 90 percent of the noncrustal V came from the coastal sources. Thistype of result is common for Narragansett during summer.

                  TABLE 7                                                         ______________________________________                                        Least-squares regional coefficients for 14                                    Narragansett aerosol samples from summer 1979                                         SO.sup.2                                                                             Regression Coefficient                                         Sample Dates                                                                            (μg m.sup.-3)                                                                       NE      BOS  NYC   WASH  INT                               ______________________________________                                        13-17 July                                                                              8.63     0.66    0.11 0.11  0.02  0.07                              17-24 July                                                                              12.32    0.37    0.26 0.12  0.01  0.20                              24-27 July                                                                              11.24    0.00    0.36 0.00  0.00  0.56                              27-31 July                                                                              19.12    0.00    0.19 0.16  0.00  0.47                              31 July-  16.49    0.76    0.00 0.04  0.00  0.34                              3 August                                                                       3-8 August                                                                             10.28    0.55    0.13 0.00  0.06  0.24                               8-10 August                                                                            5.47     0.56    0.08 0.22  0.00  0.23                              10-14 August                                                                            10.49    0.30    0.37 0.00  0.00  0.19                              14-17 August                                                                            8.31     1.17    0.07 0.19  0.00  0.00                              17-21 August                                                                            12.14    0.47    0.35 0.00  0.02  0.00                              21-24 August                                                                            22.48    0.38    0.47 0.09  0.00  0.00                              24-28 August                                                                            12.90    0.78    0.17 0.00  0.00  0.16                              28-31 August                                                                            11.00    0.80    0.05 0.02  0.00  0.14                              31 August-                                                                              8.71     0.55    0.16 0.00  0.00  0.27                              4 September                                                                   ______________________________________                                    

Table 7 summarizes the apportionments of 14 consecutive semiweeklysamples from Narragansett during summer 1979, and shows that the mix ofsources can vary strongly in response to large-scale meterology. Duringsummer 1979, Narragansett had two major sulfate episodes, one in Julyand one in August. The first was a "typical" summer episode, with windsfrom the south to west. The second episode was different, however. Ithad the highest summer sulfate seen to that time in Narragansett but thelowest (most northeastern) noncrustal Mn/V ratios and the lowest As.Meterological maps showed that this episode was the result oflarge-scale stagnation in the Northeast of air which had originatedlargely in the upper Great Lakes and Canada. Thus, the first episodeappeared to be mid-Atlantic or interior in origin, whereas the secondappeared to be more than from New England and Canada.

The apportionments bore out these observations. The first episode hadhigh regression coefficients from the interior, normal coefficients fromBoston, and low coefficients from New England. The second episode, bycontrast, had zero coefficients from the interior and normal to highcoefficients from Boston and New England. Washington aerosol wasnegligible throughout the period; contributions from the New York areawere low to moderate and irregular.

Although our tracer system is based on primary pollution elements, thatis, those emitted directly as aerosol, an important use of the systemwill be to understand the regional origins of secondary species, such assulfate and acidity, which are formed in the atmosphere from primaryprecursors. Sulfate is the most abundant constituent of many remoteaerosols, and both sulfate and acidity are of great concern in aciddeposition.

Strictly speaking, primary constituents cannot trace secondaryconstituents. Near strong sources of (primary) aerosol, such as largeurban or industrial areas, our tracer system should work poorly forsulfate. Outside such areas, where regional aerosols dominate, a primarytracer system should work better, although there may still bedifficulties. In remote areas, primary tracers should work still betterbecause most of the primary precursors, such as SO₂, will have beenconverted or otherwise removed; that is, the secondary species will havereached quasi-stable proportions. Under these conditions, the agedregional aerosols would effectively contain a sulfate component linkedto the primary signature elements.

This appears to be the situation at Underhill, Vt., for example. In aseries of 39 daily samples from July and August 1982, we determined the"effective" sulfate in the various regional signatures by firstapportioning the seven tracer elements, then regressing the sulfate ofeach sample against the regional coefficients derived from that sample.The results gave the following approximate concentrations of sulfate:21±1 g m⁻³ for the interior signature (INT), 7±3 μg m⁻³ for themid-Atlantic region (WASH), and 3±1 μg m⁻³ for the local aerosol (NE).Based on these values, the predicted sulfate concentrations generallyreproduced the observed values to within 25 percent (FIG. 2). Thisaccuracy is comparable to that obtained for the primary tracer elements.In particular, each of the peaks and valleys of sulfate was predicted.

At Narragansett, Rhode Island, however, the same approach gave poorerresults. FIG. 2 shows the observed and predicted sulfate for 21semiweekly samples during June to September 1979. The fractional errorswere twice as large as at Underhill, neither peaks or valleys werepredicted correctly, and a period of low sulfate at the beginning wasmissed entirely. This behavior is consistent with Narragansett's lessremote location and with the abundant SO₂ observed there even duringsummer (2 to 20 g m⁻³) (T. R. Fogg, personal communication). The "noise"in sulfate at Narragansett most likely results from variable andunpredictable oxidation of this subregional SO₂, on a scale too small tobe seen at Underhill. Time traces of the elements at Narragansett areconsiderably more irregular relative to each other and to sulfate thanat Underhill. Thus, it appears that both primary and secondary aerosolof the coastal Northeast are more local in origin than those in interiorNew England and that control of this aerosol and its deposition willrequire different strategies for different parts of the Northeast.

We claim:
 1. A method to determine regional sources of pollution aerosolwhich includes:(a) selecting empirically a small number of suitabletracer elements which are pollution-derived, associated withsubmicron-sized particles, and accurately analyzable in the aerosol; (b)measuring the concentrations of each tracer element in multiple samplesof regionally-representative aerosol at multiple sites in each sourceregion whose signature is to be determined; (c) expressing the measuredresults as ratios to one of the tracer elements; (d) defining theelemental signature of the source region as the collection of elementalratios and associated standard deviations which best represents thatregion's aerosol; (e) determining the source region's signature frommodes in the logarithmic frequency distributions of the elemental ratiosof samples taken in source region; (f) measuring the concentrations ofeach tracer element in multiple samples of an aerosol from a receptorregion; (g) comparing the elemental ratios from the receptor region tothe signatures from possible source regions to determine the mostprobable source region.
 2. The method of claim 1 wherein the tracerelements are selected from the group consisting essentially of As, Sb,Se, Zn, In, noncrustal Mn, noncrustal V, Pb, Cd, Ag, C, and combinationsthereof.
 3. The method of claim 1 wherein the common denominator of theelemental ratios is selected from the group consisting essentially ofSe, Zn, Pb, and C.
 4. The method of claim 1 which includes:checking thestability during transport of a regional signature determined solelywithin a region by measurements outside the region.
 5. The method ofclaim 1 which includes:identifying the perturbing effects of a localsource by performing factor analysis on the raw data from a given site;isolating the local source on its own factor; determining thecomposition of the source from that factor; and eliminating theperturbing effects of that source by considering it as a separatesignature subsequently.
 6. The method of claim 1 whichincludes:determining the most probable area of origin of unknown samplesby discriminant analysis of elemental ratios.
 7. The method of claim 1which includes:apportioning aerosol samples of mixed origin intoregional contributions by least-squares fitting of the signatures(element by element) to the sample.
 8. The method of claim 1 whichincludes:apportioning secondary constituents such as sulfate or otherprimary constituents such as elemental carbon, in a series of ratios ata single site, into regional contributions by regressing theirconcentrations against the regional coefficients of the samples.
 9. Amethod to determine regional sources of pollution aerosol whichincludes:(a) selecting empirically a small number of suitable tracerelements which are pollution-derived, associated with submicron-sizedparticles, and accurately analyzable in the aerosol; (b) measuring theconcentrations of each tracer element in multiple samples ofregionally-representative aerosol at multiple sites in each sourceregion whose signature is to be determined; (c) expressing the measuredresults as ratios to one of the tracer elements; (d) defining theelemental signature of the source region as the collection of elementalratios and associated standard deviations which best represents thatregion's aerosol; (e) determining the source region's signature from thecharacteristics of samples taken during periods of atmosphericstagnation; (f) measuring the concentrations of each tracer element inmultiple samples of an aerosol from a receptor region; (g) comparing theelemental ratios from the receptor region to the signatures frompossible source regions to determine the most probable source region.